From Big Data to smart knowledge – integrating multimodal biological data and modelling metabolism – Professor Falk Schreiber

Modern data acquisition methods in the life sciences allow the procurement of different types of data in increasing quantity, facilitating a comprehensive view of biological systems. As data is usually gathered and interpreted by separate domain scientists, it is hard to grasp multi‐domain properties and structures. Consequently there is a need for the integration, analysis, modelling, simulation, and visualisation of life science data from different sources and of different types.
This talk focuses on these two aspects: firstly, methods for the integration and visualization of multimodal biological data are presented. This is achieved based on two graphs representing the meta‐relations between biological data, and the measurement combinations, respectively. Both graphs are linked and serve as different views of the integrated data with navigation and exploration possibilities. Data can be combined and visualised multifariously, resulting in views of the integrated biological data. Secondly, methods to reconstruct, simulate, and analyse detailed metabolic models are presented. We will focus on stoichiometric models, and see how different types of data are used to gather new insights into metabolic processes shown on an example of metabolism in plants.


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